摘要
基于WEKA平台分别采用三种机器学习分类算法,构建了湖库富营养化程度的智能评价模型,分析了我国24个湖库的营养状态并进行了评价与比较。结果表明,该智能评价模型分辨率较高,建模方法简便易行、计算快捷、无需编程即能轻松实现,具有应用价值,可供借鉴。
Based on WEKA platform, the intelligent model for assessment of eutrophication is developed by three kinds of machine learning classification algorithms. The nutrient status of twenty-four representative lakes and reservoirs in China are evaluated and analyzed comparatively using the proposed models. The results show that the proposed models have high resolution in grading eutrophication of lakes and reservoirs. Especially, the modeling method is simple to calculate speed and can be easily achieved without programming. Thus, the simple and effective methods had good application value in the field of lake and reservoir eutrophication assessment, and the research results provid scientific reference for the non-computer science researchers.
出处
《水电能源科学》
北大核心
2010年第4期40-42,80,共4页
Water Resources and Power
基金
"十一五"国家科技支撑计划基金资助项目(2008BAB29B09)
国家水体污染控制与治理科技重大专项子课题基金资助项目(2008ZX07104-004)
